With maturity of cloud technologies, large-scale software systems such as a BSS/OSS system of telecommunications service providers and various service platforms have more or less defects under a traditional operation and maintenance mode: for example, high purchasing cost, a silo system, a sub-system corresponding to a set of hardware resource system such as storage, database, server, and a software binding with a hardware; low resource utilization rate, service configuration based on peak value without the capability of fully sharing resources; very long service launch cycle from proposing a new service to experiencing software development cycle as well as hardware approval and purchasing arrival period; low maintenance efficiency, high labor costs, low standardization of various systems without the capability of centralized maintenance and monitor; poor energy efficiency ratio, low device density, expanding telecommunication equipment room resources, non-environmental-friendly electricity power consumption, and the like.
As such, the industry tends to implement migration deployment of large software systems from traditional silo systems to cloud platforms, thereby solving the above-mentioned challenges. In the prior art, MapReduce (Mapreduce) is used as a software architecture to distribute large-scale concurrent computation tasks to bottom-layer resources. However, to implement real time scheduling based on MapReduce and similar technologies, a software system must be implemented by application re-architecture and development according to the framework.